Background. Although considerable progress has been made in increasing breast cancer screening rates, there remains a significant proportion of women ages 40 and older who have never had a mammogram or not had one in the last two years. Behavioral interventions to increase mammography use have not been particularly effective among rarely and never screened women. Little is known about the broader context of rarely and never screened women's lives, yet this information seems particularly promising for identifying the distinct intervention needs and capacities of these populations. This dissertation study seeks to understand why some low-income and minority women never or rarely get mammograms while other similarly disadvantaged women are up-to-date with screening. Goal. The overall study goal is to describe and compare basic needs, neighborhood SES, sense of coherence and social ties among three groups of low-income and minority women: (1) those who have never been screened for breast cancer;(2) those who have rarely been screened;and (3) those who are up-to-date. The study will quantify characteristics of women across the three groups, assess the influence of these characteristics (and their interactions) on screening behavior, and determine the relative influence of individual- and community-level characteristics on screening behavior. Study objectives are consistent with research priorities of the National Center on Minority Health and Health Disparities. Methods and evaluation. Over a 12-month period, a random sample of callers to United Way 2-1-1 Missouri will be invited to complete a cancer risk assessment and baseline survey at the end of their standard 2-1-1 call. A telephone interview will be administered to 516 female callers who are age-eligible for mammography. Women ages 40 and older will answer questions related to their use of mammography, basic needs, sense of coherence, social ties and demographic characteristics. Census tract data will be used to assess neighborhood SES. Data will be analyzed using bivariate analyses, multinomial logistic regression, structural equation modeling and hierarchical linear (multilevel) modeling. Potential contribution. Identifying characteristics associated with breast cancer screening can inform the development of effective behavioral interventions for disparity populations and help eliminate breast cancer disparities.